An early application of generative models was presented by Pathak et al. for image inpainting to reconstruct a region within an image that adapts well to its surroundings [1]}.
Shrivastava et al. proposed an approach denoted Simulated+Unsupervised (S+U) learning which allows to improve the output of a simulator based on a GAN network [2]}.
Furthermore, StarGAN was introduced by Choi et al. to improve the quality of translated images by providing a more scalable method for image-to-image translation to an arbitrary domain [3]}.
